Reinforcement Learning From Scratch: Understanding Current Approaches - with Examples in Java and Greenfoot - Hardcover

Lorenz, Uwe

Hardcover

ISBN 10: 3031090292 ISBN 13: 9783031090295

Publisher: Springer, 2022

Synopsis

In ancient games such as chess or go, the most brilliant players can improve by studying the strategies produced by a machine. Robotic systems practice their own movements. In arcade games, agents capable of learning reach superhuman levels within a few hours. How do these spectacular reinforcement learning algorithms work? 

With easy-to-understand explanations and clear examples in Java and Greenfoot, you can acquire the principles of reinforcement learning and apply them in your own intelligent agents. Greenfoot (M.Kölling, King's College London) and the hamster model (D. Bohles, University of Oldenburg) are simple but also powerful didactic tools that were developed to convey basic programming concepts. 

The result is an accessible introduction into machine learning that  concentrates on reinforcement learning. Taking the reader through the steps of developing intelligent agents, from the very basics to advanced aspects, touching on a variety of machine learning algorithms along the way, one is allowed to play along, experiment, and add their own ideas and experiments.  

About this title

About the Author

After studying computer science and philosophy with a focus on artificial intelligence and machine learning at the Humboldt University Berlin and for a few years as a project engineer, Uwe Lorenz currently works as a high school teacher for computer science and mathematics and at the Free University of Berlin in the Computing Education Research Group, - since his first contact with computers at the end of the 1980s he couldn't let go of the topic of artificial intelligence.

From the Back Cover

In ancient games such as chess or go, the most brilliant players can improve by studying the strategies produced by a machine. Robotic systems practice their own movements. In arcade games, agents capable of learning reach superhuman levels within a few hours. How do these spectacular reinforcement learning algorithms work? 

With easy-to-understand explanations and clear examples in Java and Greenfoot, you can acquire the principles of reinforcement learning and apply them in your own intelligent agents. Greenfoot (M.Kölling, King's College London) and the hamster model (D. Bohles, University of Oldenburg) are simple but also powerful didactic tools that were developed to convey basic programming concepts. 

The result is an accessible introduction into machine learning that  concentrates on reinforcement learning. Taking the reader through the steps of developing intelligent agents, from the very basics to advanced aspects, touching on a variety of machine learning algorithms along the way, one is allowed to play along, experiment, and add their own ideas and experiments.  

This book is a translation of an original German edition. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.

Edition details

• Publisher: Springer
• Publication date: 2022
• Language: English
• ISBN 10: 3031090292
• ISBN 13: 9783031090295
• Binding: Hardcover
• Edition number: 1
• Number of pages: 198